This course has been designed for people interested in extracting meaning from written English text, though the knowledge can be applied to other human languages as well.
The course will cover how to make use of text written by humans, such as blog posts, tweets, etc...
For example, an analyst can set up an algorithm which will reach a conclusion automatically based on extensive data source.
Short Introduction to NLP methods
word and sentence tokenization
text classification
sentiment analysis
spelling correction
information extraction
parsing
meaning extraction
question answering
Overview of NLP theory
probability
statistics
machine learning
n-gram language modeling
naive bayes
maxent classifiers
sequence models (Hidden Markov Models)
probabilistic dependency
constituent parsing
vector-space models of meaning

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